Ammonia adsorption is a precondition for the selective catalytic reduction (SCR) of nitrogen oxides (NO_x) to take place and it influences catalyst performance under transient conditions. For a vanadium-based SCR catalyst NH₃ adsorption takes place on multiple adsorption sites over the catalyst surface with different behaviours depending on temperature, gas concentration and catalyst oxidation state. In this study, a mechanistic NH₃ adsorption model within the framework of Langmuir adsorption models was developed for describing the NH₃ adsorption isotherms obtained with a gas flow reactor for a vanadium-based SCR. The model was created by a data-driven modeling process, which involves different steps. First, a large set of candidate models was created systematically by combining multiple feasible adsorption mechanisms. Then, a parameter estimation workflow was performed using three different objective functions with increased complexity. Finally, a model reconciliation step was executed and a quality assessment was done for creating a unified robust model with a high degree of validity. As a result of this method, an NH₃ adsorption model with five adsorption sites with different mechanisms was obtained that captures the main features from the experimental data. Furthermore, the model parameters have physical significance and relate to the adsorption strength and spatial arrangement for NH₃ and water molecules. The proposed model can be used in the development of transient models with increased validity over a wide experimental region.

_{氨吸附是发生氮氧化物 (NO x} )的选择性催化还原 (SCR) 的先决条件，它会影响瞬态条件下的催化剂性能。对于钒基 ​​SCR 催化剂，NH ₃吸附发生在催化剂表面上的多个吸附位点上，其行为取决于温度、气体浓度和催化剂氧化状态。在本研究中，在 Langmuir 吸附模型框架内开发了一种机械 NH _{3吸附模型，用于描述 NH 3}钒基 SCR 的气流反应器获得的吸附等温线。该模型是由数据驱动的建模过程创建的，该过程涉及不同的步骤。首先，通过结合多种可行的吸附机制，系统地创建了大量候选模型。然后，使用三个不同的目标函数执行参数估计工作流程，增加了复杂性。最后，执行模型协调步骤并进行质量评估，以创建具有高度有效性的统一稳健模型。作为这种方法的结果，NH ₃获得了具有不同机制的五个吸附位点的吸附模型，该模型捕捉了实验数据的主要特征。此外，模型参数具有物理意义，与NH ₃和水分子的吸附强度和空间排列有关。所提出的模型可用于开发瞬态模型，在广泛的实验区域内具有更高的有效性。